AutoSens Detroit 2022 - Agenda

The benefits of AVs can only be meaningful when deployed at scale. As Cruise moves from R&D into early commercialization, the approach to system architecture has evolved to provide for a more capable system at a cost point that enables rapid scaling. We will discuss this progression, some of the enabling technologies and paradigms, and what we anticipate for the future.

Hear from:

shane mcguire

Shane McGuire
Principal Systems Engineer, Systems Architecture

Exterior automotive imaging applications are quickly evolving, to meet customer requirements image sensor manufactures are being forced to develop new technologies.   Many of these new technologies are necessary for both human and machine vision applications.    Exterior cameras are used for rear view, surround view, e-mirror, digital video recording, ADAS and AD applications.    In this paper we will discuss the requirements and challenges associated with developing these new technologies.   Unfortunately these requirements are often conflicting forcing image sensor manufactures to make tradeoffs based on cost, size and time to market.  Specifically, we will discuss high dynamic range image capture, LED flicker mitigation, low light sensitivity, high temperature operation and cyber security.

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Boyd Fowler

Boyd Fowler

Hear from industry analysts, observers and those working directly in the autmotive sector as they explore the future of the supply chain and whether there will be consolidation in specific areas (e.g. SOCs, AD software suppliers, Lidar suppliers etc.)

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Rudy Burger
Managing Partner
Woodside Capital Partners

juergen hoellisch

Juergen Hoellisch
Hoellisch Consulting GmbH

abhay rai_internet

Abhay Rai
Senior Vice President
indie Semiconductor

chris van den elzen

Chris Van Dan Elzen
 EVP, Radar Product Area

liang downey

Liang Downey
Digital Advisor, Energy, Mobility and Sustainability Customer Transformation
Microsoft Industry Solutions
IEEE USA Women in Engineering

LiDAR remains one of the most critical sensors enabling autonomous driving. And while most agree with the criticality of this sensor, confusion remains regarding what performance is needed to address different use cases and enable different levels of autonomy.

Warren Smith, who helped develop the perception teams at Uber ATG and Aurora Innovation, will discuss LiDAR requirements from the point of view of a perception engineer. What key data is needed from the sensor and how is that data used by perception to address difficult edge cases. How does this boil down to lidar specifications and how can lidar manufacturers use this information to enable L4-L5 autonomous vehicles.

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warren smith

Warren Smith
Director of Perception
Insight LiDAR

This talk compares the characteristics of digital code modulation (DCM) radar to traditional analog modulated radars used today, such as Frequency Modulated Continuous Wave (FMCW) radars. The speaker will explain how these radar systems operate, including the transmission, reception, and the associated signal processing employed to determine the distance, velocity, and angle of objects in the environment. By comparing these two radar systems, familiarity with digital radar is enhanced and the potential advantages of digital radar are better appreciated. The speaker will introduce two benchmarks of merit: 1) High Contrast Resolution (HCR), which is critical to resolving small objects next to large objects (e.g., a child in front of a truck), and 2) Interference Susceptibility Factor (ISF), which characterizes a radar’s resilience to self-interference and cross interference. These benchmarks are essential to understanding the value of radar in use cases that are crucial to achieving increased safety for vehicle automation and autonomy.

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arunesh roy.jpg

Dr. Arunesh Roy
Senior Director Advanced Applications and Perception

It has become widely accepted that LiDAR sensors will be an indispensable part of a sensor suite that will enable vehicular autonomy in the future. However, sensor costs remain very high and prevent the ubiquitous adoption of LiDAR sensors.

Bringing knowledge and expertise in Cost-Engineering and Design for Manufacturing from the HDD space into the LiDAR space can accelerate the large-scale deployment of LiDAR sensors.
In this talk, some of the key manufacturing technologies will be highlighted.

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Zoran Jandric

Dr Zoran Jandric
Engineering Director
Seagate Technology

Regardless of Radar type, simulation of the sensor is absolutely essential to reach the goals desired for ADAS and especially levels 4-5 for AV. Some aspects of this required simulation are discussed and how to implement these aspects into a simulation correctly.

Discussion points for Radar simulation include:

  1. World Material Property measurement including Angle of Incidence
  2. Advanced Ray Tracing
  3. Micro Doppler, Ghost Targets and Doppler Ambiguity
  4. Radar placement effects (bumper, grill, etc.)

Finally, a discussion of a cutting edge Hardware-in-the-Loop for radar is also presented.

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Screenshot 2021-06-29 at 12.45.57_tony

Tony Gioutsos
Director Portfolio Development Autonomous Americas

Steering, ranging and detection are the core elements that simultaneously operate a LIDAR system. At Baraja, our LiDAR combines our patented Spectrum-Scan steering technology and unique ranging technique, Random Modulation Continuous Wave (RMCW) paired with homodyne detection, to enable a high-performance Doppler LiDAR without any of the known issues found in other LiDAR designs. This novel combination of core technologies allows for no-compromise, unprecedented LiDAR performance, reliability and integrability that will enable a fully-autonomous future without the costly trade-offs of legacy technologies.

Hear from:

Federico Collarte

Federico Collarte
Founder and CEO

Honda and, more recently, Mercedes-Benz have made history by rolling out the first level 3 vehicles on open roads. These achievements have been made possible notably thanks to one technology – LiDAR.
To bring these features to scale, LiDAR technology is undergoing 2 concurrent transitions that will
– bring the reliability and productization to automotive industry standards
– deliver uncompromising performance compared to the pre-LiDAR status quo.

Hear from:

Clement Nouvel

Clement Nouvel
LiDAR Technical Director

4D imaging radar has become a technology of choice for in-cabin safety and ADAS, favored for its high-resolution imaging, versatile field of view configurations and precise target data. But high cost, substantial hardware and extreme complexity have restricted deployment to premium models. In this thought-provoking session, we will discuss a crucial turning point for 4D imaging radar, which made it affordable and accessible to all vehicle models, supporting dozens of applications. The “Democratization of 4D Imaging Radar” is a presentation about making high-end safety available for all vehicle models.

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Dan Viza

Dan Viza
Head of US Business Development

To make the technology available for volume model vehicles, the measurement capability and reliability of LiDAR must be ensured in cost-effective production at large quantities.

A core task in mass production is the assembly of optical, mechanical, and electronic components. The precise alignment of emitting and receiving electronics with projection or imaging objective lenses plays a decisive role here. Tolerances in all components of the sensors prevent the assembly of an optomechanical system by a straightforward mounting process. Alignment requires an automated process with inline feedback on sensor performance to ensure that the required optomechanical parameters are of high quality for each device and within tight tolerances for the entire production.

The paper describes recent developments of different alignment procedures TRIOPTICS has developed for various types of LiDAR systems used in the automotive industry to ensure repeatable and reproducible quality under production requirements.

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Dirk Seebaum
Business Unit Manager

For the longest time, radar applications deployed DSPs featuring fixed point arithmetic, as floating point operations were considered to be inferior in terms of performance, power efficiency and area (PPA), which is critical for any embedded system.

Yet there has always been a desire to move to floating point arithmetic, as it allows for a larger dynamic range as required by the latest radar systems, achieving the required signal to noise ratio (SNR). This presentation will cover a detailed floating point / fixed point tradeoff analysis, featuring radar use cases.

It will also discuss the growing interest in AI enhanced radar algorithms, and how these can be enabled using a vector DSP, either standalone or combined with a tightly coupled AI accelerator. Specific focus will be given to the programming flow featuring support for TensorFlow, Caffe or ONNX.

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Markus Willems
Senior Product Manager

A discussion that will consider whether stringent OEM requirements can be met and whether it is possible to achieve functional safety and automotive-grade reliability whilst preserving modern vehicle design.

Hear from:

Kevin van der Putten

Kevin Vander Putten

amit mehta

Amit Mehta
Head of Innovation
North American Lighting

juergen hoellisch

Juergen Hoellisch
Hoellisch Consulting GmbH


Paula Jones
ibeo Automotive USA

Automotive radar has been around for decades, but over the past few years there has been a flurry of activity in the new uses of radar in the car – from new applications to exotic antennas. This talk will introduce the audience to some new radar-based applications in vehicle localization, in-cabin health monitoring, and occupancy detection as well as cover notable new approaches to classic automotive radar. We will discuss how they work, why they are useful and, in some cases, why it took so long for them to appear.

Hear from:

Harvey Weinberg

Harvey Weinberg
Director of Sensor Technologies
Microtech Ventures

There are many ways to evaluate camera image quality using standardized equipment and metrics. However, after the results are tabulated, how do you assess which camera is most suitable for your specific application?

In this presentation DXOMARK will introduce an example of evaluation benchmark protocol for Automotive camera Image Quality.

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Pierre Yves

Pierre-Yves Maitre
Senior Image Quality Engineer

The largest cost of developing artificial intelligence-based automated driving solutions is collecting and labelling data for training and validation regardless of autonomy level. Furthermore, data quality and diversity are also critical to enable truly robust and intelligent systems.

The use of synthetic and augmented data coupled with automatically annotated real-world data will be a game-changer for developing, testing and updating the next generation of Automated Driving software solutions.

This talk will discuss state-of-the-art data generation and labelling methods, introduce an integrated, cost-efficient, data-driven pipeline, and use different hardware platforms at different stages, from training to in-vehicle integration.

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Dr. Peter Kovacs
Production SVP

By developing an end-to-end optical simulation pipeline including AI, we are able determine the impact of optical parameters on learning-based approaches.

We will show how to use this method?to jointly determine post-processing image rectification and optical characteristics for optimized ADAS and autonomous driving applications.

We will demonstrate that we can ease most of the image rectification processes by directly obtaining an optimized image with a camera designed according to such optical characteristics.

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Patrice Roulet

Patrice Roulet

Recently, non-RGB image sensors gain a traction in the automotive applications. One traction is from the demand to achieve smaller pixel size with keeping low light SNR. We did a pros/cons study of the popular color filter arrays such as RCCB, RYYCy, RCCG and RGB, including the analysis of so-called Yellow / Red traffic signal differentiation issue. The other traction is from the demand to use one camera for both of Machine Vision and Human Vision purposes, especially in Driver Monitoring Systems. RGB-Ir is under study for this application.

In this presentation, we will present those color filter options and discuss what is useful for what applications.

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Dr. Eiichi Funatsu

Dr. Eiichi Funatsu
VP of Technology

The commercialisation of Autonomous Systems including autonomous cars will require rigorous methods to certify artificial intelligence and make it safe. However, no solutions or standards exist today to guide the OEM and Tier 1 companies in that challenge, which is why CS Group has invested two years of research to develop a process – based on avionics certification – that aims to make the embedded artificial intelligence functionally safe.

Hear from:

Amine Smire profile pic

Amine Smires
Director Autonomous Systems
CS Group

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